End-to-end ownership: Identify and frame ambiguous business problems, set measurable success criteria, prototype solutions, and deliver production-ready algorithms.
Algorithm design: Develop and refine methods across clustering, graph learning, causal inference, time-series modeling, and optimization to enable new product capabilities.
Workflow deep dive: Work closely with Product teams to analyze current pipelines, map data and decision flows, and identify inefficiencies and opportunities for improvement.
Real-world data modeling: Explore, structure, and model construction-related data, including progress histories and schedules. Build robust datasets and meaningful features.
Collaborate with a dynamic team of talented researchers driving digital transformation in the construction industry.
Requirements:
Adaptability to thrive in a fast-paced startup environment.
4+ years of experience solving algorithmic problems with real-world data in areas such as: Unsupervised learning & clustering, Time-series analysis, Graphs & sequences (graph algorithms, path analysis, community detection)
Strong proficiency in Python (Pandas, NumPy, scikit-learn).
Skilled in handling complex and noisy datasets.
BSc in CS, electrical engineering or similar degrees
Strong product intuition and communication skills: capable of collaborating with diverse teams, translating qualitative challenges into quantitative problem definitions, and clearly articulating trade-offs.
*By submitting your application, you agree that Buildots will process your personal data in accordance with